Operations | Monitoring | ITSM | DevOps | Cloud

Why Some IT Teams Adopt AI Faster (And How to Close The Gap)

Every IT leader is under pressure to show AI results. Budgets are approved, pilots are launched, and vendors promise transformation within a quarter. Some teams are already running AI agents in production, resolving tickets and answering employees without human intervention. Others are still stuck in proof-of-concept purgatory, six months into a rollout with nothing to show a board. The thing is, AI doesn't fix what's broken in an IT operation, it multiplies what's already there.

Called it (mostly): Checking in on 2026 predictions so far

On this episode of Masters of Data, we revisit the predictions Adam White, Zoe Hawkins, and David Girvin made at the end of last year, checking our own scorecard halfway through 2026. The hits: agents running amok and deleting databases, MCP becoming the backbone for tracking what agents actually do, growing security gaps around personal data, and a collective rejection of low-quality AI content. The misses: we underestimated how fast companies would cut staff for AI, then quietly start rehiring once the agents couldn't cover the work, and we're still arguing about whether token burn is a cost problem or a coming attack vector.

Deterministic vs Probabilistic AI Engineering Explained

Deterministic processes carry one guarantee: the same input will produce the same output. That guarantee built the entire observability stack. AI broke that contract by reasoning in terms of probability. The same input can now produce different outputs, whether from AI-generated code that carries assumptions invisible in staging, or from distributed systems where timing creates failures that no pre-captured telemetry can anticipate.

GitHub Copilot cost: what teams actually pay in 2026

The GitHub Copilot cost runs from $0 for the Free tier to $10/month for Pro, $39/month for Pro+, and $100/month for Max. Teams pay $19/user/month for Business and $39/user/month for Enterprise. The twist: on June 1, 2026 GitHub swapped fixed premium requests for usage-based AI Credits, so what those flat fees actually buy now depends on how hard you push the AI. The sticker price is the easy part. The part that ambushes finance is everything stacked on top of it.

How to Evaluate an Agentic Process Automation Platform in 2026

Agentic AI has moved quickly from experimentation to enterprise planning. IT leaders are no longer asking whether AI agents can summarize tickets; they’re asking a more important question: Can agentic AI actually complete work consistently and measurably? That is where agentic process automation becomes critical.

How to Automate Unstructured Data Using AI Agents (Clear & highly searchable)

Let’s be honest: traditional automation breaks the second it hits a scanned PDF, a messy email thread, or an architectural drawing. Rules-based RPA simply lacks the cognition required to decode unstructured data. In this episode of, Project Manager Swetha K J breaks down exactly how we conquered this massive roadblock on our automation journey. By embedding advanced AI models directly into automation workflows, we’ve built a context-aware architecture that transitions systems from static execution to dynamic intelligence.

Why individual AI adoption is breaking team-level throughput

There is a question a lot of engineering leaders are quietly sitting with right now: we have rolled out AI tools across the team, the developers seem faster, so why isn't more software actually shipping? It is a reasonable thing to consider. Pull requests are opening faster. Lines of code per sprint are up. The boilerplate that used to take full afternoons now takes minutes. By every local measure, the investment is paying off.

MCP vs CLI: Does it even make a difference? | Live Laugh Logs ep. 3

MCP vs CLI: does it even make a difference? Here’s everything you need to know. Welcome to Episode 3 of Live Laugh Logs, the podcast from the Coralogix Developer Relations team. This week Andre has made the move to the US, so Annie and Lewis are joined by George Pickers, Head of Solution Engineering for EMEA & APAC at Coralogix.